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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Ali Sajid Muhammad Noor Sultan Muhammad Muaviz Ishfaq Ali Raza Department of Mechatronics and Control Engineering Human Centered Robotics Lab of NCRA University of Engineering and Technology Lahore Lahore Pakistan

ISBN: (数字)9798350355703

ISBN: (纸本)9798350355710

Constituting to the demographic age shift in many regions of the world, technological advancement in the care sector, to deliver quality services to the elders, is now in more demand than ever. One such advancement is the evolution of socially assistive and care robots that promise sustainable, reliable, and safe human-robot interaction to meet geriatric needs. This paper presents the design and development of Silver Companion: a geriatric care robot for the elderly. The target audience chosen for the research phase is the socially isolated elderly community of East Asia and Central Europe which make up about 45% of their total elderly population. Considering the human-centered design paradigm, the technical and psychological aspects of the robot have been devised. The form and functions of the robot have been based on the product design principles. The whole development journey has been subjected to the identified elderly needs and the robot has been tested under multiple use-case scenarios, ideated for possibly fulfilling those needs. The robot has been equipped with assistive and interactive features like voice interaction, complementing micro-gestures and robot expressions, seamless navigation, and robot perception enhanced by a tilt-pan mechanism, all contributing towards making the robot capable of uplifting the well-being and quality of life of seniors.

关键词： Industries Silver Service robots Navigation Psychology Human-robot interaction Product design Reliability Older adults Geriatrics

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SYSTEMS AND APPLICATION MANAGEMENT IN HYBRID CLOUD INFRASTRUCTURES

International Journal of Mechatronics and Applied Mechanics

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International Journal of mechatronics and Applied Mechanics 2025年第19期1卷 92-99页

作者： Țîțu, Aurel Mihail Toderici, Marius Stanciu, Andreea Lucian Blaga" University of Sibiu Faculty of Engineering Industrial Engineering and Management Department 10 Victoriei Street Sibiu550024 Romania National University of Science and Technology POLITEHNICA Bucharest Faculty of Industrial Engineering and Robotics Splaiul Independentei no. 313 6th District Bucharest Romania National Institute of Research and Development in Mechatronics and Measurement Technique – INCDMTM Șos. Pantelimon Nr. 6-8 Sector 2 Bucharest21358 Romania

Hardware resource management in a hybrid IT infrastructure combines the management of public cloud resources with the management of private cloud resources that are most often owned in the organization's on-premises infrastructure. According to the IBM Transformation Index, approximately 77% of organizations have adopted a hybrid IT infrastructure in the cloud. Hybrid cloud infrastructure combines the 3 types of IT infrastructures, namely: the organization's on-premises IT infrastructure, the IT infrastructure that forms the organization's private cloud, and the public cloud that is made available by cloud service providers. This combination of IT infrastructures comes with different challenges in terms of security, hardware and software compatibility, connectivity, and interoperability, all of which are managed by the IT team. Public cloud is easier to manage than private cloud because cloud service providers take care of the maintenance of the hardware infrastructure and provide services through which users can manage the infrastructure at the level of processing, storage, memory, etc. resources. but offers less control on the security side. The management of the hardware resources to which an organization has access is important in view of the fact that this environment can accommodate different services and applications that quickly circulate data between on-premises systems and the public or private cloud and that make different services of the organization available to internal and external users. Hybrid infrastructure management has become a challenge for many organizations from both a technical, economic and human point of view. © 2025 The Author(s). Published by Cefin Publishing House – Bucharest.

关键词： Cloud platforms

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Quantifying Joint Movement Variability in Healthy and Hemiplegic Gait using OpenSim 2

Quantifying Joint Movement Variability in Healthy and Hemipl...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Rafiq, Tabassum Younis, Sadia Narayan, Jyotindra Institute of Information Management and Technology Department of Biotechnology Uttar Pradesh Aligarh202001 India Government College of Engineering and Technology Department of Biomedical Engineering Jammu and Kashmir Ganderbal193504 India Indian Institute of Technology Guwahati Mechatronics and Robotics Laboratory Department of Mechanical Engineering Assam Guwahati781039 India

ISBN: (纸本)9798350360523

This study delves into the scaling capabilities of OpenSim, a biomechanical modeling tool, to scrutinize musculoskeletal alterations accompanying the hemiplegic condition compared to a healthy model. Contralateral hemiplegia (CH), characterized by unilateral paralysis, induces profound changes in bone size and significantly influences an individual's gait. Motivated by understanding the biomechanical repercussions of CH on human movement, we conducted a comprehensive investigation involving ten patients with CH, with a median age of 46 years (range: 39 to 52.0 years and height: 1.75 0.6 m). Ten healthy controls with similar body attributes were±also recruited. We assessed musculoskeletal changes post-CH using bone length data from MRI reports obtained from a hospital. Inverse kinematics in OpenSim are facilitated for a detailed comparison of joint angles between unhealthy and healthy individuals. The gait data is visualized and analyzed using statistical metrics such as mean absolute deviation, box plots, and a two-sample t-test. The results revealed significant differences in hip and ankle joint angles between healthy and hemiplegic individuals, underscored by low p-values. Interestingly, no significant difference was observed in knee joint angles (p-value = 0.9126). These findings contribute to a valuable understanding of hemiplegia-related musculoskeletal changes, offering potential avenues for tailored interventions to improve mobility and quality of life. © 2024 IEEE.

关键词： Inverse kinematics

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A Novel Approach for Efficient Gaussian Mixture Model using Dynamics-motivated Optimal Excitation

A Novel Approach for Efficient Gaussian Mixture Model using ...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Taehoon Kim Juwon Jeong Taejune Kong Hyunwook Lee Sehoon Oh Department of Robotics and Mechatronics Engineering DGIST (Daegu Gyeongbuk Institute of Science and Technology) Daegu Republic of Korea School of Mechatronics Engineering Gyeongsang National University Jinju Republic of Korea

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

EffiDynaMix, a novel, efficient, gray-box, nonparametric dynamics modeling method, integrates mathematical dynamics with Gaussian Mixture Model (GMM) for simplified training data creation and improved generalization. It outperforms traditional methods like conv-GMM, GP, and LSTM in training efficiency and accuracy with new data. By leveraging dynamic equations, EffiDynaMix enhances learning efficiency and adaptability, offering advancements in robotic system precision and computational efficiency, leading to faster and more responsive robots.

关键词： Training Industrial electronics Adaptation models Service robots Computational modeling Training data Mathematical models

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A Robust Control Technique for Pitch Control of an Aeropendulum 6

A Robust Control Technique for Pitch Control of an Aeropendu...

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6th International Conference on robotics, Control and Automation engineering, RCAE 2023

作者： Tanveer, M. Hassan Koduru, Charles Roy, Rupam Gupta Lakhekar, Girish V. Chun, Cary Kennesaw State University Department of Robotics and Mechatronics Engineering MariettaGA30067 United States National Institute of Technology Department of Electronics and Instrumentation Engineering Agartala Barjala Jirania Tripura Agartala India College of Engineering Department of Instrumentation Engineering Maharashtra Pune India

ISBN: (纸本)9798350315301

Pitch control of an aviation system presents a plethora of control complications, such as nonlinear effects, parameter uncertainties, disturbances, etc. In the face of parametric uncertainties and disturbances, as well as communication limits in an auditory medium, it is difficult to create efficient control algorithms that can accomplish precise path-following tasks and effective resilient control actions. This paper presents the Second Order Sliding Mode Control method for regulating the pitch angle in an aero-pendulum mechatronic system. The fundamental purpose of this study is to develop a reliable controller capable of minimising the system error between the regulated signal and the planned signal that corresponds to the pitch angle of the vehicle. By employing the proposed approach, both the prevalence of chattering and the control efficiency can be greatly improved. A comparison is given between the proposed model and the classical technique now in use, such as the classical Sliding Mode Controller. © 2023 IEEE.

关键词： Sliding mode control

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Preliminary Work on Compliant Horseshoe Crab Artificial Intelligence Robot (CHAIR)

Preliminary Work on Compliant Horseshoe Crab Artificial Inte...

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IEEE Southeastcon

作者： Kate Johnson Jamie Assaf Rafael Juarez Razvan Voicu Ayse Tekes Robotics and Mechatronics Kennesaw State University Atlanta GA Mechanical Engineering Kennesaw State University Atlanta GA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

This paper introduces a compliant robot inspired from horseshoe crab that harnesses the advantages of bendable links to achieve locomotion reminiscent of its natural counterpart. Our robot design features multiple motors for dynamic limb motion and a selectively positioned tail mechanism, which, in future work, will play a pivotal role in swimming. In this initial phase, we focus on establishing fundamental terrestrial locomotion by conducting separate Q-learning experiments for forward movement, left turning, and right turning. Each experiment utilizes gyroscopic feedback to reinforce proper tilt and balance, ensuring stable movement across diverse surface conditions. The success of these individual Q-learning procedures demonstrates how a soft robotic platform can systematically learn essential gait patterns while minimizing disturbances to local ecosystems, owing to the gentle, adaptive interactions afforded by compliant materials. By utilizing bendable links, the robot can conform more closely to uneven terrain, resulting in increased stability and reduced motor strain compared to rigid-body designs. The gyroscope-driven reward structure guides the robot's posture, helping it make timely corrective adjustments for each action. Overall, these results highlight that soft robotics, coupled with reinforcement learning and orientation-based rewards, is a viable approach for developing multi-terrain robots. This work establishes a foundation for more comprehensive action discovery, eventually incorporating additional sensing modalities, continuous tail motions, and further environmental-awareness capabilities to enable fully autonomous amphibious navigation.

关键词： Q-learning Torque Tail Soft robotics Robot sensing systems Motors Turning Gyroscopes Robots Strain

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Beyond Words: Integrating Personality Traits and Context-Driven Gestures in Human-Robot Interactions 25

Beyond Words: Integrating Personality Traits and Context-Dri...

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Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems

作者： Tahsin Tariq Banna Sejuti Rahman Mohammad Tareq Robotics & Mechatronics Engineering University of Dhaka Dhaka Bangladesh Accounting & Information Systems University of Dhaka Dhaka Bangladesh

ISBN: (纸本)9798400714269

As robots become increasingly integrated into human life, personalizing human-robot interactions (HRI) is crucial for improving user acceptance, engagement, and interaction quality. However, personalizing HRI poses a unique challenge due to the diversity of human personality traits. This paper proposes a method that leverages large language models (LLMs) to dynamically tailor robot conversations according to the Big Five (OCEAN) personality traits. Our novelty lies in using user personality traits to shape robots' verbal responses and implementing contextual action generation for gestures. This study addresses two primary research questions: (1) Does adapting robots' verbal responses based on user personality traits improve communication satisfaction? (2) How does the addition of context-appropriate gestures further enhance user satisfaction? We used Goldberg's personality trait measurement scale (1992) to assess 26 participants who engaged in conversations with an LLM-powered Pepper robot on various topics. The quality of these interactions was self-reported using a revised version of Hecht's (1978) conversation satisfaction scale. Three experimental conditions were conducted: (i) Baseline: Standard LLM conversation, (ii) Personality-congruent: LLM-adjusted dialogue based on personality of participants, and (iii) Enhanced interaction: Personality adaptation plus dynamic gestures. For the third condition, we implemented contextually appropriate pre-defined animations and generated novel gestures by computing joint angle values in real time. Statistical analysis using ANOVA revealed significant differences in communication satisfaction across the three conditions (F=13.41, p<.001). Post-hoc analyses using Šidák's multiple comparison test showed significant pairwise differences: Condition 2 vs. 1: Δ Δmean 4.42, p = 0.02; Condition 3 vs. 1: Δ Δmean 8.23, p < 0.01; Condition 3 vs. 2: Δ Δmean 3.80, p = 0.05. These results demonstrate that both personality-congruent inter

关键词： HRI

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Deep Learning-Based Hash Function Cryptanalysis

Deep Learning-Based Hash Function Cryptanalysis

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Ongee Jeong Inkyu Moon Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science & Technology (DGIST) Daegu Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

This paper analyzes the strength of Message Digest Algorithm (MD5) by performing deep learning-based Encryption Emulation (EE) and Plaintext Recovery (PR) attacks. We convert randomly generated S12-bit arrays, messages, into 128-bit arrays, digests, with MD5 in different numbers of steps. Furthermore, two different structures of deep learning models, fully-connected neural network and Bidirectional Long Short-Term Memory (BiLSTM), are used in attacks and trained to analyze MD5 automatically. As a result, the BiLSTM shows better prediction accuracy than the fully-connected neural network. Moreover, the PR attack is more challenging than the EE attack.

关键词： Deep learning Analytical models Accuracy Neural networks Emulation Bidirectional long short term memory Cryptographic hash function Information and communication technology Encryption Convergence

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Comparison of Object Detection Technique for Applications in ETAT Automation Training Set 7

Comparison of Object Detection Technique for Applications in...

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7th International Conference on Information Technology, InCIT 2023

作者： Kosiyanurak, Karin Singsri, Pongpat Seangsri, Soontaree Promput, Sommart Rajamangala University of Technology Tawan-ok School of Engineering and Innovation Department of Mechatronics and Robotics Engineering Chonburi Thailand Rajamangala University of Technology Tawan-ok Faculty of Science and Technology Department of Information and Communication Technology Chonburi Thailand

ISBN: (纸本)9798350358698

Object detection is a type of artificial intelligence (AI) that is currently being developed and used widely. It can classify and detect objects in images or videos. This research aims to investigate object detection that is suitable and accurate for detecting the color of the workpieces in the training set. This study will experiment comparison of three object detection models: 1. OpenCV Python code via the Thonny software. Using the BGR color separation principle, the range of color values must be specified so that the model can separate different colors. 2. V4-tiny and 3. V7-tiny are models that use model training principles in the CiRA-CORE Platform. In this study, 1,271 images of workpieces processed with the Augmentation Technique were utilized to train the model. and 240 images for testing the model. To analyze of find a suitable and accurate model for detecting the color of workpieces Because light is important in visual or object detection in real-time this study divided the experiment into two conditions: LED Lighting and without LED Lighting. The results showed that V7-tiny is an object detection model that can detect the color of the target in both lighting conditions. The V7-tiny model has an accuracy of 97.92%. © 2023 IEEE.

关键词： Object detection

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Privacy-Preserving Classification of Photon-Limited Images Using Deep Learning

Privacy-Preserving Classification of Photon-Limited Images U...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Ongee Jeong Inkyu Moon Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science & Technology (DGIST) Daegu Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

This paper presents a privacy-preserving image classification scheme based on deep learning and photon counting imaging. The vision transformer-based deep learning model can classify the photon-limited color images, which represents the images sparsely by using a few photons. As a result, over 90 % of photon-limited images can be classified when at least 50,000 photons are used. Since some information from the original images is lost in the photon-limited images, it is challenging to recognize the personal information in the photon-limited images. Therefore, the proposed scheme can classify the images while concealing the portion of the information in the images.

关键词： Deep learning Image recognition Imaging Color Transformers Information and communication technology Photonics Image classification Convergence

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